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Localization is an essential problem in autonomous navigation of self-driving cars. We present a monocular vision based approach for localization in urban environments using road markings. We utilize road markings as landmarks instead of traditional visual features (e.g. SIFT) to tackle the localization problem because road markings are more robust against changes in perspective, illumination, and...
Large lighting variation challenges all visual odometry methods, even with RGB-D cameras. Here we propose a line segment-based RGB-D indoor odometry algorithm robust to lighting variation. We know line segments are abundant indoors and less sensitive to lighting change than point features. However, depth data are often noisy, corrupted or even missing for line segments which are often found on object...
An efficient numerical method is developed to analyze light transmission through subwavelength apertures in metallic films, where the apertutres can have arbitrary cross sections and be surrounded by many grooves. The method is tailor-made for three-dimensional structures that are layered in different regions. It relies on field expansions in one-dimensional vertical modes, and boundary integral equations...
For the scattering of light by cylindrical metallic nanoparticles on a substrate, we present an efficient numerical method that relies on expanding the field in one-dimensional vertical modes. The method is used to analyze a single cylin-drical particle of arbitrary cross section and a pair of circular cylindrical particles.
Segmentation and mapping of planar building facades (PBFs) can increase a robot's ability of scene understanding and localization in urban environments which are often quasi-rectilinear and GPS-challenged. PBFs are basic components of the quasi-rectilinear environment. We propose a passive vision-based PBF segmentation and mapping algorithm by combining both appearance and geometric constraints. We...
We present a high level landmark-based visual navigation approach for a monocular mobile robot. We utilize heterogeneous features, such as points, line segments, lines, planes, and vanishing points, and their inner geometric constraints as the integrated high level landmarks. This is managed through a multilayer feature graph (MFG). Our method extends local bundle adjustment (LBA)-based framework...
We develop algorithms that can assist robot to perform building exterior mapping, which is important for building energy retrofitting. In this task, a robot needs to identify building facades in its localization and mapping process, which in turn can be used to assist robot navigation. Existing localization and mapping algorithms rely on low level features such as point clouds and line segments and...
Buildings consume around 40% of overall energy in the world. Planar mirror detection problem (PMDP) arises when surveying reflective building surface for building energy retrofit. PMDP is also important for collision avoidance when robots navigate close to highly reflective glassy walls. Our approach uses two views from an on-board camera. First, we derive geometric constraints for corresponding real-virtual...
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